Initial validation of GOCI water products against in situ data collected around Korean peninsula for 2010-2011
This paper provides initial validation results for GOCI-derived water products using match-ups between the satellite and ship-borne in situ data for the period of 2010-2011, with a focus on remote-sensing reflectance ( R rs ). Match-up data were constructed through systematic quality control of both in situ and GOCI data, and a manual inspection of associated GOCI images to identify pixels contaminated by cloud, land and inter-slot radiometric discrepancy. Efforts were made to process and quality check the in situ R rs data. This selection process yielded 32 optimal match-ups for the R rs spectra, chlorophyll a concentration (Chl_ a) and colored dissolved organic matter (CDOM), and with 20 match-ups for suspended particulate matter concentration (SPM). Most of the match-ups are located close to shore and thus the validation should be interpreted limiting to near-shore coastal waters. The R rs match-ups showed the mean relative errors of 18-33% for the visible bands with the lowest 18-19% for the 490 nm and 555 nm bands and 33% for the 412 nm band. Correlation for the R rs match-ups was high in the 490-865 nm bands (R2=0.72-0.84) and lower in the 412 nm band (R2=0.43) and 443 nm band (R2=0.66). The match-ups for Chl_ a showed a low correlation (<0.41) although the mean absolute percentage error was 35% for the GOCI standard Chl_ a. The CDOM match-ups showed an even worse comparison with R2<0.2. These match-up comparison for Chl_ a and CDOM would imply the difficulty to estimate Chl_ a and CDOM in near-shore waters where the variability in SPM would dominate the variability in R rs . Clearly, the match-up statistics for SPM was better with R2=0.73 and 0.87 for two evaluated algorithms, although GOCI-derived SPM overestimated low concentration and underestimated high concentration. Based on this initial match-up analysis, we made several recommendations -1) to collect more offshore under-water measurements of the R rs data, 2) to include quality flags in level-2 products, 3) to introduce an ISRD correction in the GOCI processing chain, 4) to investigate other types of in-water algorithms such as semianalytical ones, and 5) to investigate vicarious calibration for GOCI data and to maintain accurate and consistent calibration of field radiometric instruments.